Evaluation of African-American and White Racial Classification in a Surveillance, Epidemiology, and End Results Cancer Registry

Objectives: This study evaluated the validity of registry-reported race for individuals who participated in research studies conducted since 1980 through the Metropolitan Detroit Cancer Surveillance System (MDCSS), a Surveillance, Epidemiology, and End Results (SEER) Program registry. Methods: 5329 individuals who self-identified as African American or White and were classified in the MDCSS registry as African American or White were included. Self-identified and registry-reported race were compared, and associations between demographics and racial misclassification were examined. Results: Most self-identified African Americans and Whites were correctly classified (sensitivity= 98.5%, specificity=99.7%). Males were two times more likely to be misclassified than females [odds ratio (OR)=2.13, 95% confidence interval (CI): 1.06-4.29]. Individuals diagnosed with cancer after 1990 were two times more likely to be misclassified than those diagnosed before 1990 (OR= 2.17, 95% CI: 1.07--4.42). African Americans were four times more likely to be misclassified than Whites (OR=4.39, 95% CI: 2.24-8.60). Conclusions: Misclassification in the MDCSS registry of African Americans as Whites, and vice versa, is relatively low. Additional studies should evaluate misclassification of African Americans and Whites as other races and/or ethnicities in the SEER registry

Family history of prostate and colorectal cancer and risk of colorectal cancer in the Women's health initiative.

BackgroundEvidence suggests that risk of colorectal and prostate cancer is increased among those with a family history of the same disease, particularly among first-degree relatives. However, the aggregation of colorectal and prostate cancer within families has not been well investigated.MethodsAnalyses were conducted among participants of the Women's Health Initiative (WHI) observational cohort, free of cancer at the baseline examination. Subjects were followed for colorectal cancer through August 31st, 2009. A Cox-proportional hazards regression modeling approach was used to estimate risk of colorectal cancer associated with a family history of prostate cancer, colorectal cancer and both cancers among first-degree relatives of all participants and stratified by race (African American vs. White).ResultsOf 75,999 eligible participants, there were 1122 colorectal cancer cases diagnosed over the study period. A family history of prostate cancer alone was not associated with an increase in colorectal cancer risk after adjustment for confounders (aHR =0.94; 95% CI =0.76, 1.15). Separate analysis examining the joint impact, a family history of both colorectal and prostate cancer was associated with an almost 50% increase in colorectal cancer risk (aHR = 1.48; 95% CI = 1.04, 2.10), but similar to those with a family history of colorectal cancer only (95% CI = 1.31; 95% CI = 1.11, 1.54).ConclusionsOur findings suggest risk of colorectal cancer is increased similarly among women with colorectal cancer only and among those with both colorectal and prostate cancer diagnosed among first-degree family members. Future studies are needed to determine the relative contribution of genes and shared environment to the risk of both cancers

Lung Cancer Screening Criteria and Cardiopulmonary Comorbidities

INTRODUCTION: Lung cancer screening criteria should select candidates with minimal cardiopulmonary comorbidities who are fit for curative lung cancer resection. METHODS: We retrospectively analyzed 728 patients with lung cancer for screening eligibility using the U.S. Preventive Services Task Force (USPSTF) 2013 criteria (n = 370). If ineligible for screening, they were further assessed for eligibility using the USPSTF 2021 (n = 121) and National Comprehensive Cancer Network group 2 (NCCN gp 2) (n = 155). Comparisons of cardiopulmonary comorbidities between patients selected by the different lung cancer screening criteria were performed. Excluding missing data, a similar comparison was done between USPSTF 2013 (n = 283) and PLCOm2012 (risk threshold ≥1.51%) (n = 118). RESULTS: Patients eligible for USPSTF 2021 and NCCN gp 2 had lower rates of airflow obstruction (forced expiratory volume in 1 s [FEV1]/forced vital capacity \u3c0.7) compared with those in USPSTF 2013 (55.4% and 56.8% versus 70.5%). Both USPSTF 2021 and NCCN gp 2 groups had less severe airflow obstruction; only 11.6% and 12.9% of patients, respectively, had percent-predicted FEV1 less than 50% versus 20.3% in the USPSTF 2013 group. Comparing USPSTF 2013 and PLCOm2012 revealed no significant differences in age or the rate of airflow obstruction (p = 0.06 and p = 0.09 respectively). Nevertheless, rates of percent-predicted FEV1 less than 50% and diffusing capacity of the lungs for carbon monoxide less than 50% were lower in the PLCOm2012 group compared with those in the USPSTF 2013 group (22.3% versus 10.2% and 32.6% versus 20.0%), respectively. CONCLUSIONS: The USPSTF 2021 qualifies an additional group of screening candidates who are healthier with better lung reserve, translating to better surgical candidacy but potentially more overdiagnosis. The PLCOm2012, with its better accuracy in selecting patients at risk of cancer, selects an older group with chronic obstructive pulmonary disease but with good lung reserve and potentially less overdiagnosis

Genetic variation in Glutathione S-Transferase Omega-1, Arsenic Methyltransferase and Methylene-tetrahydrofolate Reductase, arsenic exposure and bladder cancer: a case–control study

Abstract Background Ingestion of groundwater with high concentrations of inorganic arsenic has been linked to adverse health outcomes, including bladder cancer, however studies have not consistently observed any elevation in risk at lower concentrations. Genetic variability in the metabolism and clearance of arsenic is an important consideration in any investigation of its potential health risks. Therefore, we examined the association between genes thought to play a role in the metabolism of arsenic and bladder cancer. Methods Single nucleotide polymorphisms (SNPs) in GSTO-1, As3MT and MTHFR were genotyped using DNA from 219 bladder cancer cases and 273 controls participating in a case–control study in Southeastern Michigan and exposed to low to moderate (\u3c50 μg/L) levels of arsenic in their drinking water. A time-weighted measure of arsenic exposure was constructed using measures from household water samples combined with past residential history, geocoded and merged with archived arsenic data predicted from multiple resources. Results While no single SNP in As3MT was significantly associated with bladder cancer overall, several SNPs were associated with bladder cancer among those exposed to higher arsenic levels. Individuals with one or more copies of the C allele in rs11191439 (the Met287Thr polymorphism) had an elevated risk of bladder cancer (OR = 1.17; 95% CI = 1.04-1.32 per 1 μg/L increase in average exposure). However, no association was observed between average arsenic exposure and bladder cancer among TT homozygotes in the same SNP. Bladder cancer cases were also 60% less likely to be homozygotes for the A allele in rs1476413 in MTHFR compared to controls (OR = 0.40; 95% CI = 0.18-0.88). Conclusions Variation in As3MT and MTHFR is associated with bladder cancer among those exposed to relatively low concentrations of inorganic arsenic. Further investigation is warranted to confirm these findings

Genetic variation in Glutathione S-Transferase Omega-1, Arsenic Methyltransferase and Methylene-tetrahydrofolate Reductase, arsenic exposure and bladder cancer: a case–control study

Abstract Background Ingestion of groundwater with high concentrations of inorganic arsenic has been linked to adverse health outcomes, including bladder cancer, however studies have not consistently observed any elevation in risk at lower concentrations. Genetic variability in the metabolism and clearance of arsenic is an important consideration in any investigation of its potential health risks. Therefore, we examined the association between genes thought to play a role in the metabolism of arsenic and bladder cancer. Methods Single nucleotide polymorphisms (SNPs) in GSTO-1, As3MT and MTHFR were genotyped using DNA from 219 bladder cancer cases and 273 controls participating in a case–control study in Southeastern Michigan and exposed to low to moderate (<50 μg/L) levels of arsenic in their drinking water. A time-weighted measure of arsenic exposure was constructed using measures from household water samples combined with past residential history, geocoded and merged with archived arsenic data predicted from multiple resources. Results While no single SNP in As3MT was significantly associated with bladder cancer overall, several SNPs were associated with bladder cancer among those exposed to higher arsenic levels. Individuals with one or more copies of the C allele in rs11191439 (the Met287Thr polymorphism) had an elevated risk of bladder cancer (OR = 1.17; 95% CI = 1.04-1.32 per 1 μg/L increase in average exposure). However, no association was observed between average arsenic exposure and bladder cancer among TT homozygotes in the same SNP. Bladder cancer cases were also 60% less likely to be homozygotes for the A allele in rs1476413 in MTHFR compared to controls (OR = 0.40; 95% CI = 0.18-0.88). Conclusions Variation in As3MT and MTHFR is associated with bladder cancer among those exposed to relatively low concentrations of inorganic arsenic. Further investigation is warranted to confirm these findings.http://deepblue.lib.umich.edu/bitstream/2027.42/112833/1/12940_2012_Article_570.pd

Tobacco smoking as a risk factor of bronchioloalveolar carcinoma of the lung: pooled analysis of seven case–control studies in the International Lung Cancer Consortium (ILCCO)

Background: The International Lung Cancer Consortium (ILCCO) was established in 2004, based on the collaboration of research groups leading large molecular epidemiology studies of lung cancer that are ongoing or have been recently completed. This framework offered the opportunity to investigate the role of tobacco smoking in the development of bronchioloalveolar carcinoma (BAC), a rare form of lung cancer. Methods: Our pooled data comprised seven case–control studies from the United States, with detailed information on tobacco smoking and histology, which contributed 799 cases of BAC and 15,859 controls. We estimated the odds ratio of BAC for tobacco smoking, using never smokers as a referent category, after adjustment for age, sex, race, and study center. Results: The odds ratio of BAC for ever smoking was 2.47 (95% confidence interval [CI] 2.08, 2.93); the risk increased linearly with duration, amount, and cumulative cigarette smoking and persisted long after smoking cessation. The proportion of BAC cases attributable to smoking was 0.47 (95% CI 0.39, 0.54). Conclusions: This analysis provides a precise estimate of the risk of BAC for tobacco smoking

Risk Factors Associated with a Second Primary Lung Cancer in Patients with an Initial Primary Lung Cancer

Objectives: Increased patient survivorship following initial primary lung cancer (IPLC) due to advancing clinical practice has uncovered new clinical challenges. With growing patient longevity, individuals post-IPLC continue to be at higher subsequent risk of developing secondary primary lung cancer (SPLC). Proper SPLC surveillance guidelines aimed at monitoring IPLC survivors is crucial to enhancing life expectancy in this population. This study aims to categorize risk factors associated with SPLC emergence in IPLC survivors for clinical use following IPLC treatment. Materials and Methods: Using the Karmanos Cancer Institute Tumor Registry, patients diagnosed with IPLC from 2000 to 2017 were identified. Patients diagnosed with SPLC were matched for histology, age and stage to individuals who did not develop SPLC. Logistic and Cox regression analyses were performed to identify potential risk factors for SPLC emergence and overall survival. Results: 121 patients diagnosed with IPLC who later developed SPLC were identified and compared to 120 patients with IPLC who did not develop SPLC. Patients who did not undergo surgical resection had a significantly lower probability of developing SPLC (OR 0.235, 95% confidence interval [CI]: 0.118 to 0.450; p\u3c0.001). Compared to surgical resection patients, individuals who did not have surgery as their primary treatment for IPLC had a significantly higher hazard of death (HR 3.088, 95% CI: 2.114 to 4.512; p\u3c0.001). Conclusion: This study uncovered notable associations and lack thereof between several competing risk factors and SPLC development as well as mortality. Further characterization of SPLC risk factors is essential for implementing effective surveillance recommendations

Breast-Cancer-Specific Mortality in Patients Treated Based on the 21-Gene Assay: A SEER Population-Based Study

The 21-gene Recurrence Score assay is validated to predict recurrence risk and chemotherapy benefit in hormone-receptor-positive (HR+) invasive breast cancer. To determine prospective breast-cancer-specific mortality (BCSM) outcomes by baseline Recurrence Score results and clinical covariates, the National Cancer Institute collaborated with Genomic Health and 14 population-based registries in the the Surveillance, Epidemiology, and End Results (SEER) Program to electronically supplement cancer surveillance data with Recurrence Score results. The prespecified primary analysis cohort was 40–84 years of age, and had node-negative, HR+, HER2-negative, nonmetastatic disease diagnosed between January 2004 and December 2011 in the entire SEER population, and Recurrence Score results (N = 38,568). Unadjusted 5-year BCSM were 0.4% (n = 21,023; 95% confidence interval (CI), 0.3–0.6%), 1.4% (n = 14,494; 95% CI, 1.1–1.7%), and 4.4% (n = 3,051; 95% CI, 3.4–5.6%) for Recurrence Score \u3c 18, 18–30, and ≥ 31 groups, respectively (P \u3c 0.001). In multivariable analysis adjusted for age, tumor size, grade, and race, the Recurrence Score result predicted BCSM (P \u3c 0.001). Among patients with node-positive disease (micrometastases and up to three positive nodes; N = 4,691), 5-year BCSM (unadjusted) was 1.0% (n = 2,694; 95% CI, 0.5–2.0%), 2.3% (n = 1,669; 95% CI, 1.3–4.1%), and 14.3% (n = 328; 95% CI, 8.4–23.8%) for Recurrence Score \u3c 18, 18–30, ≥ 31 groups, respectively (P \u3c 0.001). Five-year BCSM by Recurrence Score group are reported for important patient subgroups, including age, race, tumor size, grade, and socioeconomic status. This SEER study represents the largest report of prospective BCSM outcomes based on Recurrence Score results for patients with HR+, HER2-negative, node-negative, or node-positive breast cancer, including subgroups often under-represented in clinical trials

Natural and Orthogonal Interaction framework for modeling gene-environment interactions with application to lung cancer

Objectives: We aimed at extending the Natural and Orthogonal Interaction (NOIA) framework, developed for modeling gene-gene interactions in the analysis of quantitative traits, to allow for reduced genetic models, dichotomous traits, and gene-environment interactions. We evaluate the performance of the NOIA statistical models using simulated data and lung cancer data. Methods: The NOIA statistical models are developed for additive, dominant, and recessive genetic models as well as for a binary environmental exposure. Using the Kronecker product rule, a NOIA statistical model is built to model gene-environment interactions. By treating the genotypic values as the logarithm of odds, the NOIA statistical models are extended to the analysis of case-control data. Results: Our simulations showed that power for testing associations while allowing for interaction using the NOIA statistical model is much higher than using functional models for most of the scenarios we simulated. When applied to lung cancer data, much smaller p values were obtained using the NOIA statistical model for either the main effects or the SNP-smoking interactions for some of the SNPs tested. Conclusion: The NOIA statistical models are usually more powerful than the functional models in detecting main effects and interaction effects for both quantitative traits and binary traits. Copyright (C) 2012 S. Karger AG, Base